EP2235477A1 - Estimation de plus court chemin dépendant du temps dans un réseau routier - Google Patents
Estimation de plus court chemin dépendant du temps dans un réseau routierInfo
- Publication number
- EP2235477A1 EP2235477A1 EP09704762A EP09704762A EP2235477A1 EP 2235477 A1 EP2235477 A1 EP 2235477A1 EP 09704762 A EP09704762 A EP 09704762A EP 09704762 A EP09704762 A EP 09704762A EP 2235477 A1 EP2235477 A1 EP 2235477A1
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- European Patent Office
- Prior art keywords
- node
- nodes
- cell
- graph
- oriented
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- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags or using precalculated routes
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
Definitions
- the present invention relates to an estimation of a shorter path in travel time depending on a given start time and the evolution of traffic in a road network, called the shortest path dependent on time.
- it relates to a determination of a path very close to the shortest path according to the travel time taking into account, during the real-time journey, the evolution of the traffic on a road network whose travel time on a given arc is predictable in the future.
- Traffic information systems provide historical speeds or travel times expressing traffic conditions on road sections. These histories are determined from information continuously recorded in the field by various means such as fixed sensors, or mobile sensors in vehicles. Statistical analysis methods determine stable and very realistic profiles of highly probable traffic characteristics at a given start time. Some processes rely on calendar information such as the day of the week or the date of the school holidays. This information is grouped in the histories in heterogeneous classes. For example, every Monday of the school year is grouped together in one class and every Monday of the vacation is grouped into another class. An average profile is extracted from each of these classes summarizing the different situations observed according to the days. Finer processes rely intrinsically on the observed data to form the classes. Whatever the process of profile construction, observation of real traffic conditions and calendar variables allows to get closer to the corresponding real profile and predict with a good probability the future traffic status in the short, medium or long term. .
- time-dependent shortest the shortest path between two points of the road network by considering the evolution of traffic in real time during the journey.
- time-dependent shortest path "in English).
- This determination is theoretically implemented by the Dijkstra algorithm. In practice, however, Dijkstra's algorithm is too slow for real-time applications. On a very large road network represented by many nodes interconnected by arcs, for example about ten million nodes for the road network in a country like France, several seconds are necessary to determine a single path.
- the object of the invention is to reduce the determination time of a shorter path dependent on time.
- the invention for estimating the shortest path in travel time dependent on a given start time between a source node and a destination node belonging to an oriented graph representative of a a road network and covered with cells containing nodes of the graph and arcs oriented between the nodes, each oriented arc being associated with predicted travel times evolving over time and depending on historical traffic measurements, is characterized in that it comprises: a pretreatment of the oriented graph, determining for each pair of a start cell and an arrival cell, a sub-graph containing nodes and arcs oriented between said nodes forming paths each connecting the one of the nodes contained in the starting cell to one of the nodes contained in the arrival cell and each having a total travel time less than a threshold, and a determination of the shortest path at the given start time between the source node and the destination node, passing through nodes belonging to one of the previously determined sub-graphs relating to the pair of cells whose starting cell is such that at the given start time the path from the source node to the core node of the
- the journey times of the paths are dependent on the predicted travel times of the oriented arcs forming the paths, these provisional journey times evolving dynamically over time.
- the pretreatment of the method of the invention has the advantage of increasing the speed of determination of the shortest path between a node. source and destination node of the directed graph by applying only one of the subgraphs determined during pretreatment relative to the pair of start and end cells to a short path determination algorithm. Preprocessing decreases the time of the determination of the shortest way since for this one all the oriented graph corresponding to the whole of the road network is not used.
- the threshold relating to this pair is defined as a function of the shortest travel time.
- the travel times used correspond to limits greater than the travel times on the oriented arcs.
- the size of each sub-graph is determined during the preprocessing phase according to the determined threshold, and thus limits the number of nodes to be explored during the determination of the shortest path between the source node and the destination node. The maximum time for determining a shorter path between a source node and a destination node can be estimated from this limitation.
- determining the shortest path between the source node and the destination node may include determining, from among all the cells of the graph, the starting cell whose shortest path from the node source to the central node of the start cell has a shortest travel time compared to path times from the source node to central nodes of the other cells of the graph at the given start time.
- the invention also relates to an estimation device for estimating the shortest path in travel time depending on a given start time between a source node and a destination node belonging to an oriented graph representative of a road network. and covered with cells containing nodes of the graph and arcs oriented between the nodes, each oriented arc being associated with predictive travel times evolving over time and depending on historical traffic measurements.
- the device is characterized in that it comprises means for performing preprocessing of the oriented graph, determining for each pair of a start cell and an arrival cell a subgraph containing nodes and nodes.
- arcs oriented between said nodes forming paths each connecting one of the nodes contained in the starting cell to one of the nodes contained in the arrival cell and each having a total travel time less than a threshold, and a means to determine the shortest path at the given start time between the source node and the destination node, passing through nodes belonging to one of the previously determined sub-graphs relating to the pair of cells whose starting cell is such that at the given start time the path from the source node to the central node of the start cell is the most short in travel time compared to paths from the source node to central nodes of other cells, and the arrival cell contains the destination node.
- the invention relates to a computer program capable of being implemented in a computing device such as the device for estimating a shorter path depending on the travel time according to the invention.
- the program includes instructions which, when the program is executed in said device, perform the steps according to the method of the invention.
- FIG. 1 is a schematic block diagram of a device for estimating the shortest path according to the invention
- FIG. 2 is a graph of arcs and nodes respectively associated with the sections of a road network;
- Figures 3 and 4 are algorithms relating to a pretreatment included in the method according to the invention;
- FIG. 5 is an algorithm relating to a determination of the shortest time-dependent path between two intersections of the road network included in the method of the invention.
- a device for estimating a shorter path DEC in a road network comprises a central processing unit UC, a preprocessing module PRT, a determination module for the shortest path DC, a BD database, a sub-graph memory Msg and a path memory Mp.
- the device for estimating the shortest path DEC according to the invention is for example included in a personal computer or a server.
- the functional blocks of the device DEC shown in FIG. 1 provide functions relating to the invention and can correspond to software and / or hardware modules.
- the device DEC is included in or connected to a road navigation system, for example on board a vehicle or included in portable radiocommunication terminals, such as personal digital assistant PDAs (smartphones) or PDAs. navigation, to determine routes in the road network.
- a road navigation system for example on board a vehicle or included in portable radiocommunication terminals, such as personal digital assistant PDAs (smartphones) or PDAs. navigation, to determine routes in the road network.
- the DEC device periodically receives traffic information measured and recorded by measuring equipment or broadcast by a server, and including forecast information, such as calendar information, determined from processing on permanent readings from the measurement equipment of traffic in the field, classified and updated in historical measures and expressing traffic conditions on sections of the road network.
- forecast information such as calendar information
- the central processing unit UC such as a processor, controls the execution of the method by activating and deactivating the pretreatment module PTR and the DC path determination module, and is connected to or integrates the aforementioned components in the device. .
- the database BD is linked to the device DEC, that is to say it is either integrated in the device DEC, or incorporated into a database management server and connected to the device DEC by a local or remote link.
- the database BD includes in particular information necessary for the operation of the device DEC of the invention such as forecast information classified in measurement histories, and map data of the road network characterizing a graph of GRT-oriented arcs representing the road network. , defined below.
- BD for its processing in the DEC device in the form of a GRT oriented graph (N, A, Fc) having a set N of nodes with
- a given moment corresponds for example to a specific time of a specific day: a Monday to
- Each node is designated by an identifier and each arc is designated by an identifier.
- a node N n represents an intersection at the junction of two or more sections of the road network. Intersections of roads and streets such as intersections, interchanges and junctions are represented by nodes.
- An arc oriented Ai, 2 represents a direction of circulation on a respective road section extending between two nodes Ni and N 2 .
- a two-way road considered as a section between two nodes, for example the nodes N u and N v , is represented by a first arc A U; V oriented from the node N u to the node N v , and by a second arc A V; U oriented from node N v to node N u .
- the function Fc such as a sinusoidal function, has a value varying over the course of time representative of predicted travel time profiles for each section corresponding to each oriented arc of the graph and according to each given instant.
- a lower bound Bi nf and an upper bound B sup to the function Fc respectively corresponding to a minimum estimated travel time and a maximum estimated travel time on the section, deduced in particular from the report of the length of the road section associated with the arc on respectively minimum and maximum projected circulation speeds to travel the section.
- the values related to the function Fc and the limits Bi nf and B sup are deduced in particular from the forecast information dynamically evolving over time as a function of road traffic, classified in historical traffic measurement records and stored in the database. Each arc is then associated with different predicted journey times on the same section according to respectively given times and in dependence on historical traffic measurements.
- the GRT graph is divided into cells Ci to C 0 that can overlap and thus have one or more nodes in common.
- Two cells Ci and C j are delimited in Figure 1, with 1 ⁇ i ⁇ C and
- Each cell for example the cell Ci, comprises a subset of connected nodes whose central node NCi is different from those of the other cells.
- the cell Ci is associated with two respective travel times ⁇ i and Oi, respectively corresponding to the travel time of the longest of the shortest paths from a node of the cell Ci to the central node NCi, and to the travel time of the longest time. shorter paths from the central node NCi to a node of the cell Ci.
- the travel times ⁇ i and Oi are predetermined in known manner by application of the Dijkstra algorithm on the graph GRT (N, A, B sup ) in which the weight of each oriented arc is determined as a function of the upper bound B sup associated with each arc.
- the PRT pretreatment module applied to the GRT graph determines subgraphs SGi, i-SGi, c to SGc, i-SGc, c respectively from all the combinations of cell pairs Ci to Cc of the GRT graph. More particularly, a subgraph SGi, j is determined from a pair of cells (Ci, C j ) formed by a starting cell Ci and an arrival cell C j , with l ⁇ i ⁇ C and l ⁇ j ⁇ C. For example in Figure 2, the subgraph SGi, j comprises the cells Ci and C j and gray nodes.
- a first algorithm AD in the pretreatment module PRT establishes according to a known Dijkstra method, for each pair of cells (Ci, C j ) of the graph GRT a first table Tb-ti, j and a second temporary table Tb-rti, j .
- the first table contains for each node N n , with 1 ⁇ n ⁇
- the second temporary table contains for each node N n , with 1 ⁇ n ⁇ N, the shortest travel time rt [N n ] of a path since the node N n towards the central node NC j of the arrival cell C j , determined from the GRT graph (N, A, Bi nf ) in which the weight of each oriented arc is determined according to the lower bound Bi nf associated with each bow.
- the pretreatment module PTR also uses a preprocessing algorithm AP which determines for each pair of cells (Ci, C j ) an associated subgraph SGi, j as a function of a threshold of travel time Hi, j determined at from the travel time table Tb-ti, j established during the execution of the algorithm AD.
- a preprocessing algorithm AP which determines for each pair of cells (Ci, C j ) an associated subgraph SGi, j as a function of a threshold of travel time Hi, j determined at from the travel time table Tb-ti, j established during the execution of the algorithm AD.
- the subgraph SGi, j is stored in the subgraph memory Msg in association with an identifier of the pair of cells (Ci, C j ).
- the travel time table Tb-ti, j , the inverse travel time table Tb-rti, j and the travel time threshold Hi, j are temporarily stored in the sub-graph memory Msg in association with an identifier of the pair of cells (Ci, C j ) and are deleted from the memory Msg at the end of the execution of the preprocessing algorithm AP.
- each travel time t [N n ], rt [N n ], relative to a node N n is registered in association with an identifier of the node N n .
- the DC path determination module includes a path determination algorithm CH which estimates the shortest path W, i.e. the path having the shortest travel time, between a source node N s and a node of destination N ⁇ of the graph GRT, relying, more particularly, on the subgraph associated with the pair of cells such that the arrival cell contains the node N ⁇ and the starting cell is determined according to a given start time of the path from the source node N s .
- the source node N s is not necessarily contained in the initial cell.
- the shortest determined path W is stored in the path memory Mp.
- the module DC establishes during the execution of the algorithm CH, a first travel time table Tb-t s , d of the path W to be determined and which contains the travel times of the nodes explored during the execution of the CH algorithm.
- the module DC also establishes a table of parent nodes Tb-P 3 , ⁇ ⁇ containing the identifiers of the nodes preceding each of the nodes belonging to the determined path W between the source node N 3 and the destination node N ⁇ .
- the identifiers of the parent nodes belonging to the path W are registered in the table Tb-P 3 ⁇ d in association with the identifiers of the nodes of the path W to which they are connected by an oriented arc.
- the method for estimating the shortest path depending on the travel time comprises a preprocessing PT executed by the pretreatment module PRT facilitating the execution of an algorithm for determining the shortest path CH by the determination module DC.
- the pretreatment PT comprises steps PTO to PT10, whose steps PT1 to PT3 and PT6 to PT9 correspond to the incrementation of two nested loops of index i and j, with l ⁇ i ⁇ C and l ⁇ j ⁇ C and i ⁇ j, to treat all possible combinations of cell pairs Ci, C j .
- the indices i and j are initialized to 1.
- step PT6 if the index j is not equal to the number of cells C of the graph GRT, then it is incremented by one unit at a time.
- step PT7 if the incremented index j is different from the index i; otherwise it is incremented by two units in steps PT7 and PT3 when the index j is equal to i-1 so as not to execute the processing of a pair of two same cells in steps PT4 and PT5.
- the index j is equal to the number C in step PT6 and if the index i has not reached C-I in step PT8, the index i is incremented by one unit in step PT9 and the index j is reset to 1 in step PT2.
- step PT8 if both indices i and j are equal to C, then the preprocessing is completed in step PT10.
- a processing is performed on the pair of cells (Ci, C j ) identified by the value of the indices i and j.
- the pretreatment module PTR executes the known algorithm of Dijkstra AD in the step PT4, in order to establish for the pair of cells (Ci, C j ) of the graph GRT the travel time table Tb-ti, j containing for each node identifier N n of the GRT graph the shortest travel time t [N n ] of a path connecting the central node NCi of the starting cell Ci to the identified node N n .
- the travel times t [N ⁇ ] at t [NN] are determined by applying the Dijkstra algorithm to the GRT graph (N, A, Bi nf ) in which the weight of each arc stored in the database BD is determined according to the lower bound Bi nf associated with each arc.
- the travel time between a central node of the cell Ci on a continent to a node N n on an island can not be determined.
- the next step PT5 is described in more detail with reference to FIG. 4 and determines, according to the table Tb-ti, j and according to the travel time threshold Hi, j previously determined, the subgraph SGi, j containing all the nodes that may be included when determining a shorter path connecting one of the nodes of the starting cell Ci to one of the nodes of the arrival cell C j .
- the travel time table Tb-ti, j , the inverse travel time table Tb-rti, j and the travel time threshold Hi, j are deleted from the sub-graph memory Msg after the execution of the step PT5.
- the pretreatment algorithm AP is based on Dijkstra's algorithm for some steps and comprises steps AP0 to AP16.
- Different sets and parameters intervene during the execution of the AP algorithm are in particular a set Q of Nq nodes that remain to be explored, with 1 ⁇ q ⁇
- the set Q initially comprises only the central node NC j of the arrival cell C j , the sets E and SGi, j are empty, the stop parameter is at a binary value FALSE, and the inverse time rt [NC j ] of the central node NC j in the inverse time table Tb-rti, j is set to zero.
- the pretreatment module PRT extracts from the table Tb-ti, j and analyzes the shortest transit time value t [NC j ] between the central node NCi of the starting cell Ci and the node central NC j of the arrival cell C j determined from the graph GRT (N, A, Bi nf ).
- Step AP2 is the beginning of a first AP2-AP16 recursion loop relating to the first exploration of nodes, then arcs.
- the module PTR continues the execution of the algorithm AP by the step AP4.
- the PTR module extracts from the set Q, a node N x whose inverse travel time rt [N x ] to connect the node NC j to the node N x is the smallest of the reverse travel times rt [Nq] associated with the nodes Nq belonging to the set Q.
- the node N x corresponds to the only node included in the set Q, the node NC j .
- the pretreatment module PTR inserts the node N x in the set of explored nodes E in step AP5.
- step AP6 the module PTR checks whether the sum of the inverse travel time rt [N x ] between the node N x and the central node NC j of the arrival cell C j and the travel time t [N x ] between the central node NCi of the starting cell Ci and the node N x is less than the threshold of the travel time Hj_, j . If rt [N x ] + t [N x ] ⁇ Hj_, j , then the node N x is inserted into the result set SGi, j to step AP7. If rt [N x ] + t [N x ]> Hi, j , in step AP6, then the node N x is not inserted into the result set SGi, j .
- step AP8 the module PTR checks whether the inverse travel time rt [N x ] connecting the node N x to the central node NC j is greater than the travel time threshold Hi, j . If rt [N x ]> Hi, j , then the PTR module sets the Stop parameter to the binary value TRUE, in step AP9. This condition relating to the time threshold Hi, j limits the algorithm AP to the processing of nodes near a possible path W to be determined later connecting one of the nodes of the starting cell Ci to one of the nodes of the arrival cell C j . If rt [N x ] ⁇ Hi, j , in step AP6, the Off parameter remains at the FALSE binary value.
- the steps AP10 to AP16 correspond to a second recursion loop which is included in the first recursion loop and during which the preprocessing module PTR processes all the arcs which connect the node N x to another node N y , with 1 ⁇ y ⁇
- the module PTR processes another arc originating from the node N x by executing the step APl 6 , a knot belonging to the set E being considered as being explored by the module PTR.
- the NTP module performs the AP12 step.
- the time rt [N y ] is recorded by overwriting the previous value in the inverse travel time table Tb-rti, j .
- the module PRT then inserts the node N y in the set Q of the nodes to be explored, the set Q thus comprising all the nodes connected to the node N x being explored, which have not yet been explored.
- the module PRT compares the sum rt [N x ] + E> i nf (N x , N y ) to the inverse travel time rt [ N y ] at step AP14. If the sum rt [N x ] + Bi nf (N x , N y ) is strictly less than the inverse travel time rt [N y ] then, in step AP15, the travel time rt [N y ] is again determined analogously to the step AP13 and recorded by overwriting the old value in the table Tb-rti, j .
- step AP16 if all the arcs connected to the node N x have not been processed, the module PTR repeats the steps API1 to AP16 of the second recurrence loop to process another unprocessed arc originating from the node N x . If all the arcs originating from node N x have been processed, the module PTR returns to step AP2 to check the conditions of stopping the first recursion loop.
- the module PTR executes the step AP3 by memorizing the set SGi, j considered as a sub-graph in the sub-graph memory Msg and exits the AP algorithm to the step PT5.
- the algorithm for determining the shortest path CH between a source node N s and a destination node N ⁇ with a given start time To comprises steps CHO to CH14, some of which rely on the algorithm Dijkstra; this algorithm is applied to the graph GRT (N, A, Fc).
- the CH algorithm comprises two phases of treatment.
- a first processing phase determines the starting cell whose path from the source node N s to the central node of the start cell at the given start time To is the shortest, that is to say having the shortest travel time compared to path times from source node N s to central nodes of other cells.
- the first phase of running processing is defined in the algorithm CH by a parameter Ph equal to 1. Once the initial cell is determined, the parameter Ph goes to 2 to trigger a second phase of treatment.
- This second processing phase determines the shortest path W in time between the source node N s and the destination node N d included in the sub-graph relating to the pair (start cell, arrival cell called destination cell ci -after), the destination cell C d being known initially.
- the set Q initially comprises only the source node N s
- the set E is empty
- an index j is set to the value of the index of a destination cell C d including the node at destination N d
- an index i corresponding to the index of a starting cell is initially set to zero
- the parameter Ph defining the processing phase of the algorithm CH is initially set to 1.
- An ordered set result W considered as the path to be determined between the source node N s and the destination node N d is initially empty.
- a travel time table Tb-t s , d is created in the memory Mp and progressively contains the travel times of the various nodes explored during the execution of the algorithm CH, these travel times being recorded in association with the identifiers respective nodes explored.
- the table Tb-t s , d contains a first path time t [N s ] of zero associated with the identifier of the source node N s .
- step CH1 which is at the beginning of a first recursion loop CH1-CH13 relative to the exploration of nodes, then arcs, the DC module extracted from the set Q, a node N x whose travel time t [N x ] to connect the node N s to the node N x at the given start time To is the smallest of the travel times t [Nq] associated with nodes Nq belonging to the set Q.
- the node N x corresponds to the only node included in the set Q, the node N s .
- the module DC inserts the node N x in the set of explored nodes E in step CH2.
- step CH3 the module DC compares the identifier of the node N x extracted with the identifier of a central node NC C of a cell C c read in the database BD. If the two identifiers do not match, the module DC enters step CH5 in a second recursion loop CH5-CH12 which is included in the first recursion loop and in which the module DC processes all the arcs connecting the node N x to another node N y , with 1 ⁇ y ⁇
- step CH6 the module DC checks in particular if the parameter Ph is equal to 1, or checks other conditions if Ph is equal to 2, which will be presented with reference to the second processing phase.
- step CH7 for an arc A X; y , if the node N y belongs to the set of explored nodes E, the module DC processes another arc originating from node N x by executing step CH12, a node belonging to the set E being considered as already explored.
- step CH7 step if the node N is not for the set E, the DC module performs the step CH8.
- the time t [N y ] is recorded in the travel time table Tb-t s , d in association with the identifier of the node N y .
- the module DC then inserts the node N y in the set Q of the nodes to be explored.
- the DC module stores in the parent node table Tb-P 3 , ⁇ ⁇ the identifier of the node Ny in association with the identifier of the node Nx, the node Ny being considered as the parent node of the node Nx in the path W.
- the module DC compares the sum t [N x ] + Fc (N x , Ny, t [N x ] + To) with the time of course t [N y ] at step CH10.
- step CHIl If the sum t [N x ] + Fc (N x , Ny, t [N x ] + To) is strictly less than the travel time t [N y ] then, in step CHIl, the travel time t [ N y ] is again determined analogously to step CH9 and recorded by overwriting the old value in the table Tb-t s , d - On the other hand, if t [N x ] + Fc (N x , Ny , t [N x ] + To)> t [N y ], the value of the travel time t [N y ] is not changed.
- the module DC saves in the parent node table tb-P s , d the identifier of the node N y in association with the identifier of the node N x , the node N y being considered as the parent node of the node N x in the path W. If another node has previously been identified as a parent node, the module DC deletes from the table tb-P s , d / the identifier of said parent node in association with the identifier of the node N x .
- step CH12 succeeding step CH7, CH9, CH10, or CH11, if all the arcs connected to the node N x have not been processed, the module DC repeats the steps CH6 to CH12 of the second recursion loop. to treat another arc starting from the node N x . If all the arcs originating from the node N x have been processed, the module DC executes the step CH13 to check if the identifier of the extracted node N x is identical to the identifier of the destination node N d . If N x ⁇ N d , then the DC module returns to step CH1, in order to extract another node to explore from the set Q.
- the cell C c is considered as the starting cell and the DC module leaves the first phase of processing to trigger the second phase of processing comprising a determination of the shortest time path between the source node N s near the central node of the starting cell Ci and the destination node N d of the destination cell C j on the basis of subgraph SGi, j relating to the two cells Ci and C j , predetermined during preprocessing PT and stored in the subprogram memory Msg.
- the node N y belongs to the set SGi, i considered as the subgraph relating to the pair (starting cell, destination cell), or if the node N y is included in the destination cell C j .
- CH12 of the second recursion loop to treat another arc originating from node N x .
- step CH13 if the identifier of the extracted node N x is identical to the identifier of the destination node N ⁇ , the module DC determines from the parent table the shortest path by writing in the set W the identifiers of the nodes of the path starting with the identifier of the destination node N ⁇ .
- the DC module searches first, in the Tb-P 3 table, ⁇ ⁇ , the identifier of the parent node p [N ⁇ ] of the destination node N ⁇ to write it in the ordered set W as a result of the identifier of the destination node N ⁇ , then look up the identifier of the parent node p [p [N ⁇ ]] of the previously written node p [N ⁇ ] in the set W and so on, until the write the identifier of the source node N 3 in the set W.
- the set W is stored in the path memory Mp.
- the invention described here relates to a method and a device for estimating the shortest path in travel time depending on a given start time between a source node and a destination node.
- the steps of the method of the invention are determined by the instructions of a computer program incorporated into a computing device such as the shorter path estimation device DEC.
- the program comprises program instructions which, when said program is executed in a processor of the device whose operation is then controlled by the execution of the program, carry out the steps of the method according to the invention.
- the invention also applies to a computer program, in particular a computer program recorded on or in a computer-readable information medium and any data processing device, adapted to implement the computer program. 'invention.
- This program can use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code such as in a partially compiled form, or in any other form desirable to implement the method according to the invention.
- the information carrier may be any entity or device capable of storing the program.
- the medium may comprise storage means or recording medium on which is recorded the computer program according to the invention, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a USB key, or a magnetic recording means, for example a floppy disk or a hard disk.
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Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| FR0800366A FR2926880B1 (fr) | 2008-01-24 | 2008-01-24 | Estimation de plus court chemin dependant du temps dans un reseau routier |
| PCT/EP2009/050806 WO2009092812A1 (fr) | 2008-01-24 | 2009-01-23 | Estimation de plus court chemin dépendant du temps dans un réseau routier |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| EP2235477A1 true EP2235477A1 (fr) | 2010-10-06 |
| EP2235477B1 EP2235477B1 (fr) | 2012-04-04 |
Family
ID=39790055
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP09704762A Not-in-force EP2235477B1 (fr) | 2008-01-24 | 2009-01-23 | Estimation de plus court chemin dépendant du temps dans un réseau routier |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP2235477B1 (fr) |
| AT (1) | ATE552477T1 (fr) |
| FR (1) | FR2926880B1 (fr) |
| WO (1) | WO2009092812A1 (fr) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9354070B2 (en) | 2013-10-31 | 2016-05-31 | Crown Equipment Corporation | Systems, methods, and industrial vehicles for determining the visibility of features |
| FR3030854A1 (fr) * | 2014-12-19 | 2016-06-24 | Thales Sa | Procede et systeme de generation d'une trajectoire de roulage au sol d'un aeronef dans un domaine aeroportuaire, produit programme d'ordinateur associe |
Families Citing this family (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011004026A2 (fr) | 2009-07-09 | 2011-01-13 | Tomtom International Bv | Appareils de navigation et procédés exécutés sur ces appareils |
| US9109909B2 (en) | 2009-07-09 | 2015-08-18 | Tomtom International B.V. | Navigation devices |
| EP3309514A1 (fr) | 2010-04-23 | 2018-04-18 | TomTom International B.V. | Dispositifs de navigation et leurs procédés mis en uvre |
| US8660789B2 (en) * | 2011-05-03 | 2014-02-25 | University Of Southern California | Hierarchical and exact fastest path computation in time-dependent spatial networks |
| US8566030B1 (en) | 2011-05-03 | 2013-10-22 | University Of Southern California | Efficient K-nearest neighbor search in time-dependent spatial networks |
| FR2992060B1 (fr) | 2012-06-19 | 2015-04-10 | Mediamobile | Methode d'estimation d'un temps de parcours d'un vehicule dans un reseau routier |
| US9404760B2 (en) | 2014-08-04 | 2016-08-02 | Xerox Corporation | Efficient route planning in public transportation networks |
| US10572847B2 (en) | 2014-10-10 | 2020-02-25 | Conduent Business Services, Llc | Dynamic space-time diagram for visualization of transportation schedule adherence |
| US9536210B2 (en) | 2014-12-11 | 2017-01-03 | Xerox Corporation | Origin-destination estimation system for a transportation system |
| US11562300B2 (en) | 2016-06-10 | 2023-01-24 | Conduent Business Services, Llc | System and method for optimal automated booking of on-demand transportation in multi-modal journeys |
| CN110260871A (zh) * | 2019-04-17 | 2019-09-20 | 太原理工大学 | 一种面向区域威胁的兵力机动环境建模方法 |
| CN111220158B (zh) * | 2020-01-15 | 2022-09-09 | 哈尔滨工程大学 | 一种基于时间方位历程图的线谱目标运动参数估计方法 |
| US12516954B2 (en) * | 2024-01-31 | 2026-01-06 | Toyota Jidosha Kabushiki Kaisha | Road graph generation |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR2677756B1 (fr) * | 1991-06-13 | 1995-04-28 | Peugeot | Procede et dispositif de calcul d'un itineraire de navigation, notamment pour vehicule automobile. |
| DE59811014D1 (de) * | 1997-10-27 | 2004-04-22 | Siemens Ag | Verfahren und anordnung zur rechnergestüzten bearbeitung eines graphen |
| US6192314B1 (en) * | 1998-03-25 | 2001-02-20 | Navigation Technologies Corp. | Method and system for route calculation in a navigation application |
| JP2003233768A (ja) * | 2002-02-12 | 2003-08-22 | Univ Tokyo | 複数経路探索のためのデュアルダイキストラ法 |
| US9076332B2 (en) * | 2006-10-19 | 2015-07-07 | Makor Issues And Rights Ltd. | Multi-objective optimization for real time traffic light control and navigation systems for urban saturated networks |
| GB2443472A (en) * | 2006-10-30 | 2008-05-07 | Cotares Ltd | Method of generating routes |
-
2008
- 2008-01-24 FR FR0800366A patent/FR2926880B1/fr not_active Expired - Fee Related
-
2009
- 2009-01-23 AT AT09704762T patent/ATE552477T1/de active
- 2009-01-23 WO PCT/EP2009/050806 patent/WO2009092812A1/fr not_active Ceased
- 2009-01-23 EP EP09704762A patent/EP2235477B1/fr not_active Not-in-force
Non-Patent Citations (1)
| Title |
|---|
| See references of WO2009092812A1 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9354070B2 (en) | 2013-10-31 | 2016-05-31 | Crown Equipment Corporation | Systems, methods, and industrial vehicles for determining the visibility of features |
| FR3030854A1 (fr) * | 2014-12-19 | 2016-06-24 | Thales Sa | Procede et systeme de generation d'une trajectoire de roulage au sol d'un aeronef dans un domaine aeroportuaire, produit programme d'ordinateur associe |
Also Published As
| Publication number | Publication date |
|---|---|
| FR2926880B1 (fr) | 2010-09-10 |
| FR2926880A1 (fr) | 2009-07-31 |
| ATE552477T1 (de) | 2012-04-15 |
| WO2009092812A1 (fr) | 2009-07-30 |
| EP2235477B1 (fr) | 2012-04-04 |
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